Submit a comment
Abstract
Advanced phenotyping of cardiovascular diseases has evolved with the application of high-resolution omics screening to populations enrolled in large-scale observational and clinical trials. This strategy has revealed that considerable heterogeneity exists at the genotype, endophenotype, and clinical phenotype levels in cardiovascular diseases, a feature of the most common diseases that has not been elucidated by conventional reductionism. In this discussion, we address genomic context and (endo)phenotypic heterogeneity, and examine commonly encountered cardiovascular diseases to illustrate the genotypic underpinnings of (endo)phenotypic diversity. We highlight the existing challenges in cardiovascular disease genotyping and phenotyping that can be addressed by the integration of big data and interpreted using novel analytical methodologies (network analysis). Precision cardiovascular medicine will only be broadly applied to cardiovascular patients once this comprehensive data set is subjected to unique, integrative analytical strategies that accommodate molecular and clinical heterogeneity rather than ignore or reduce it.
Authors
Jane A. Leopold, Bradley A. Maron, Joseph Loscalzo
Guidelines
The Editorial Board will only consider comments that are deemed relevant and of interest to readers. The Journal will not post data that have not been subjected to peer review; or a comment that is essentially a reiteration of another comment.
- Comments appear on the Journal’s website and are linked from the original article’s web page.
- Authors are notified by email if their comments are posted.
- The Journal reserves the right to edit comments for length and clarity.
- No appeals will be considered.
- Comments are not indexed in PubMed.
Specific requirements
- Maximum length, 400 words
- Entered as plain text or HTML
- Author’s name and email address, to be posted with the comment
- Declaration of all potential conflicts of interest (even if these are not ultimately posted); see the Journal’s conflict-of-interest policy
- Comments may not include figures
Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)